46 machine-learning-"https:"-"https:"-"https:"-"https:"-"https:"-"https:"-"https:" positions at University of Oslo
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-fellow-in-deep-learning-for-subsurface-imaging Where to apply Website https://www.jobbnorge.no/en/available-jobs/job/290391/postdoctoral-research-fel… Requirements Research FieldComputer scienceEducation
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on intelligent observing systems using machine learning and data assimilation methods in the ACTIVATE project. For more information and how to apply: https://www.jobbnorge.no/en/available-jobs/job/289326
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, machine learning and mathematical modelling. The centre has numerous collaborations with leading biomedical research groups internationally and in Norway. About the position The candidate will be part of
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research project Expertise in machine learning Additional expertise in one or more of the following: digital signal processing, statistics, multimodal processing, FAIR data management, music theory
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Fellow should acquire. UiO is responsible for following up on the career plan and ensuring that the Postdoctoral Fellow has access to career guidance throughout the postdoctoral term. If the Postdoctoral
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public defence are eligible for appointment Strong programming and artificial intelligence/machine learning skills Interest in creative or artistic applications. Documentary evidence would be beneficial
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measurement quality issues related to respondent non-compliance in ecological momentary assessment or exploring the use of machine learning techniques to aid the estimation of item response theory (IRT) models
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or exploring the use of machine learning techniques to aid the estimation of item response theory (IRT) models in small samples. The appointment is a full-time position and is made for a period of three years
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positions within their disciplines. A career plan shall be developed for the Postdoctoral Fellow, specifying the competencies the Postdoctoral Fellow should acquire. UiO is responsible for following up
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. The position is based at the Department of Informatics, University of Oslo, and will be part of a growing research agenda at the intersection of geographic information systems, epidemiology, machine learning and